Book Image

Cloud Analytics with Google Cloud Platform

By : Sanket Thodge
Book Image

Cloud Analytics with Google Cloud Platform

By: Sanket Thodge

Overview of this book

With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machine learning and deep learning. By the end of this book, you will have a better understanding of cloud analytics as a concept as well as a practical know-how of its implementation
Table of Contents (16 chapters)
Title Page
Packt Upsell
Foreword
Contributors
Preface
Index

Google BigQuery


Google BigQuery is a framework created by Google that helps to execute SQL-like queries on vast amounts of data at great speeds. Your own dataset can be uploaded to BigQuery, or for sandbox play, some other dataset can be used. The Results can be captured and stored on Google Cloud or can be downloaded as a CSV/Excel file on a local system.

Google BigQuery is a data warehouse framework that resolves problems by enabling super­fast SQL queries, using the execution power of Google's infra services. Also, any data can be updated or monitored based on the business needs. It can even provide others the ability to view or execute some queries on the data. BigQuery can be accessed by using a web User Interface or command-line argument; you can even make calls to the BigQuery REST API using a variety of client libraries such as Java, .NET, or Python. Also there are a variety of third-party tools that you can use to interact with BigQuery for visualizing or loading data.

Storing data...